Literature Review on Wireless Sensing—Wi-Fi Signal-Based Recognition of Human Activities

With the rapid development and wide deployment of wireless technology, Wi-Fi signals have no longer been confined to the Internet as a communication medium. Wi-Fi signals will be modulated again by human actions when propagating indoors, carrying rich human body state information. Therefore, a novel wireless sensing technology is gradually emerging that can realize gesture recognition, human daily activity detection, identification, indoor localization and human body tracking, vital signs detection, imaging, and emotional recognition by extracting effective feature information about human actions from Wi-Fi signals. Researchers mainly use channel state information or frequency modulated carrier wave in their current implementation schemes of wireless sensing technology, called “Walls have eyes”, and these schemes cover radio-frequency technology, signal processing technology, and machine learning. These available wireless sensing systems can be used in many applications such as smart home, medical health care, search-and-rescue, security, and with the high precision and passively device-free through-wall detection function. This paper elaborates the research actuality and summarizes each system structure and the basic principles of various wireless sensing applications in detail. Meanwhile, two popular implementation schemes are analyzed. In addition, the future diversely application prospects of wireless sensing systems are presented.

[1]  Kewei Chen,et al.  Neural correlates of heart rate variability during emotion , 2009, NeuroImage.

[2]  M. Reinders,et al.  Multi-Dimensional Dynamic Time Warping for Gesture Recognition , 2007 .

[3]  Ian B Hickie,et al.  Heart rate variability is associated with emotion recognition: direct evidence for a relationship between the autonomic nervous system and social cognition. , 2012, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.

[4]  Friedemann Reinhard,et al.  Holography of Wi-fi Radiation. , 2017, Physical review letters.

[5]  David Wetherall,et al.  802.11 with multiple antennas for dummies , 2010, CCRV.

[6]  Xu Chen,et al.  Tracking Vital Signs During Sleep Leveraging Off-the-shelf WiFi , 2015, MobiHoc.

[7]  L. Lucy An iterative technique for the rectification of observed distributions , 1974 .

[8]  Frans C. A. Groen,et al.  Feature-based human motion parameter estimation with radar , 2008 .

[9]  Jie Wu,et al.  A Robust Sign Language Recognition System with Sparsely Labeled Instances Using Wi-Fi Signals , 2017, 2017 IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS).

[10]  Yang Xu,et al.  WiFinger: talk to your smart devices with finger-grained gesture , 2016, UbiComp.

[11]  Kaishun Wu,et al.  WiFall: Device-free fall detection by wireless networks , 2017, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[12]  Carlo Tomasi,et al.  Perceptual metrics for image database navigation , 1999 .

[13]  Rafael A. Calvo,et al.  Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications , 2010, IEEE Transactions on Affective Computing.

[14]  Shwetak N. Patel,et al.  Whole-home gesture recognition using wireless signals , 2013, MobiCom.

[15]  Rob Miller,et al.  Smart Homes that Monitor Breathing and Heart Rate , 2015, CHI.

[16]  Yasushi Makihara,et al.  The largest inertial sensor-based gait database and performance evaluation of gait-based personal authentication , 2014, Pattern Recognit..

[17]  David Wetherall,et al.  Predictable 802.11 packet delivery from wireless channel measurements , 2010, SIGCOMM '10.

[18]  U. Rajendra Acharya,et al.  Heart rate variability: a review , 2006, Medical and Biological Engineering and Computing.

[19]  Parth H. Pathak,et al.  WiWho: WiFi-Based Person Identification in Smart Spaces , 2016, 2016 15th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN).

[20]  Fadel Adib,et al.  See through walls with WiFi! , 2013, SIGCOMM.

[21]  Wei Wang,et al.  Keystroke Recognition Using WiFi Signals , 2015, MobiCom.

[22]  Everette S. Gardner,et al.  Exponential smoothing: The state of the art , 1985 .

[23]  Frédo Durand,et al.  Capturing the human figure through a wall , 2015, ACM Trans. Graph..

[24]  Isabelle Guyon,et al.  An Introduction to Variable and Feature Selection , 2003, J. Mach. Learn. Res..

[25]  Rob Miller,et al.  3D Tracking via Body Radio Reflections , 2014, NSDI.

[26]  Elisabeth André,et al.  Emotion recognition based on physiological changes in music listening , 2008, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[27]  Lawrence Wai-Choong Wong,et al.  Indoor localization with channel impulse response based fingerprint and nonparametric regression , 2010, IEEE Transactions on Wireless Communications.

[28]  Jie Yang,et al.  E-eyes: device-free location-oriented activity identification using fine-grained WiFi signatures , 2014, MobiCom.

[29]  Fadel Adib,et al.  Multi-Person Localization via RF Body Reflections , 2015, NSDI.

[30]  Woo Chaw Seng,et al.  A review of biometric technology along with trends and prospects , 2014, Pattern Recognit..

[31]  J. P. Park The Identification Of Multiple Outliers , 2000 .

[32]  J B King,et al.  Gait Analysis. An Introduction , 1992 .

[33]  Fadel Adib,et al.  Emotion recognition using wireless signals , 2016, MobiCom.